Model-based selective layer-centric testing

Abstract

Model-based testing of large systems usually requires decomposition of the model into hierarchical submodels for generating test sequences, which fulfills the goals of module testing, but not those of system testing. System testing requires test sequences be generated from a fully resolved model, which necessitates refining the toplevel model, that is, by replacing its elements with submodels they represent. If the depth of model hierarchy is high, the number of test sequences along with their length increases resulting in high test costs. For solving this conflict, a novel approach is introduced that generates test sequences based on the top-level model and replaces elements of these sequences by corresponding, optimized test sequences generated by the submodels. To compensate the shortcoming at test accuracy, the present approach selects components that have lowering impact on the overall system reliability. The objective is to increase the reliabilities of these critical components by intensive testing and appropriate correction which, as a consequence, also increases the overall reliability at less test effort without losing accuracy. An empirical study based on a large web-based commercial system is performed to validate the approach and analyze its characteristics, and to discuss its strengths and weaknesses. © 2018 Information Processing Society of Japan.